From Virtual Patients to Digital Twins: Advancing Personalized Radiopharmaceutical Therapy

Forum Details

Date: Friday, July 17, 2026

Speakers: Greeshma Agasthya, PhD from Georgia Institute of Technology

Current radiopharmaceutical therapy is largely delivered using standardized treatment regimens, with patient-specific dosimetry performed primarily in selected clinical settings to retrospectively estimate absorbed dose to organs at risk and assess treatment safety. Although this represents an important step toward personalized care, retrospective dosimetry provides limited guidance for predicting treatment response or optimizing therapy. Achieving these goals requires scalable computational models that make patient-specific prediction clinically feasible.

We are developing a multiscale computational framework for radiopharmaceutical therapy that integrates mechanistic models across biological scales to predict treatment response. Within this framework, we are identifying the dominant sources of uncertainty, determining how they propagate across scales, and leveraging these insights to develop predictive, computationally efficient digital twins. This approach links patient-specific physiology, radiation transport, dosimetry, and biological response within a unified computational framework.

Ultimately, our goal is to shift radiopharmaceutical therapy practice from retrospectively assessing delivered dose to prospectively predicting treatment response and optimizing therapy.